A new publication co-authored by Dr. Hagai Tapiro and Prof. Yisrael Parmet.

So often are we reminded about distraction from devices, cell phones or earphones. Yet, the environment we walk in can also have a detrimental effect on our road crossing safety. In this study we show that:

Distractions in the road environment put pedestrians at risk when crossing the road.

Pedestrian’s visual attention is affected by the façade of the street.

Younger children are at higher risk when distracted.

Visual distractions are more detrimental than auditory distractions.

Abstract: Pedestrians are subject to an increasing number of stimuli and distractions derived from the roadside environment. Although the effect of distractions on child road crossing ability was recognized, there has been no systematic exploration of the effects of roadside distractions on child road crossing behavior. This work was aimed at studying the effect of roadside distractions on pedestrian road crossing behavior, focusing on elementary school-aged children, who are less capable of making a safe road crossing decision and are more vulnerable to the effect of distractions. Three types of audio distractions (a. sudden, momentary, and prominent noise, b. multiplicity of auditory elements, and c. continuous loud noise) and similar three types of visual distractions were pre-defined. Fifty-two children (aged 7–13) and adults arrived at the dome virtual reality laboratory and viewed 20 simulated crossing scenarios, embedded with visual and auditory distractions, and decided on the appropriate time to start crossing the virtual road. The results demonstrate that when exposed to environmental distractions, participants chose smaller crossing gaps, took more time to make crossing decisions, were slower to respond to the crossing opportunity, and allocated less visual attention to the peripheral regions of the road. Those effects were age related, and affected younger participants more significantly. Furthermore, visual distractions affected pedestrian behavior more than auditory type distractions. This study highlights an issue not yet adequately addressed, and the results should be considered by transportation professionals, and road safety educators, so better road safety programs to educate children can be created.

Link to the manuscript: Anyone clicking on this link before May 19, 2018 will be taken directly to the final version of your article on ScienceDirect. No sign up, registration or fees are required – they can simply click and read.https://authors.elsevier.com/c/1Wobl3IVV9Z8ir

Child pedestrians are highly represented in fatal and severe road crashes and differ in their crossing behavior from adults. Although many children carry cell phones, the effect that cell phone conversations have on children’s crossing behavior has not been thoroughly examined. A comparison of children and adult pedestrians’ crossing behavior while engaged in cell phone conversations was conducted. In a semi-immersive virtual environment simulating a typical city, 14 adults and 38 children (11 children aged 7-8; 18 aged 9-10 and 9 aged 11-13), experienced road crossing related traffic-scene scenarios. They were requested to press a response button whenever they felt it was safe to cross. Eye movements were tracked. Results have shown that all age groups’ crossing behaviors were affected by cell phone conversations. When busy with more cognitively demanding conversation types, participants were slower to react to a crossing opportunity, chose smaller crossing gaps, and allocated less visual attention to the peripheral regions of the scene. The ability to make better crossing decisions improved with age, but no interaction with cell phone conversation type was found. The most prominent improvement was shown in ‘safety gap’; each age group maintained a longer gap than its predecessor younger age group. In accordance to the current study, it is safe to say that cell phone conversations can hinder child and adult pedestrians’ safety. Thereby, it is important to take those findings in account when aiming to train young pedestrians for road-safety and increase public awareness.

Highlights

we explored child-pedestrians’ HP skills employing hazard detection task in virtual settings (our Dome lab). We used the same approach that we have used previously in the driving HP domain to study novice drivers. As pedestrians’ age increased their awareness toward potential hazards increased. 7–9-year-olds reported less instances of FOV obscured by parked vehicles. 7–9-year-olds lingered more in identifying instances of FOV obscured by parked vehicles.

Abstract

Background. Child-pedestrians are more prone to fail in identifying hazardous situations. Aiming to better understand the development of hazard-perception abilities in dynamic road situations we examined participants’ hazard detection abilities in a virtual environment.

Method. Experienced-adult participants and child-pedestrians observed typical road crossing related scenarios from a pedestrian’s point of view and engaged in a hazard detection task.

Results. Consistent with our hypotheses, less instances of obscured field of view by parked vehicles were reported as hazardous by 7–9-year-olds, who were also prone to linger more in identifying situations depicting field of view partially obscured by parked vehicles compared to all other age groups. Reports of obscured field of view by road curvature as hazardous increased with age.

Conclusions. Understanding child-pedestrians’ shortcomings in evaluating traffic situations contribute to the effort of producing intervention techniques which may increase their attentiveness toward potential hazards and lead toward reduction in their over-involvement in crashes.

Abstract

Children are over-represented in road accidents, often due to their limited ability to perform well in road crossing tasks. The present study examined children’s visual search strategies in hazardous road-crossing situations. A sample of 33 young participants (ages 7-13) and 21 adults observed 18 different road-crossing scenarios in a 180° dome shaped mixed reality simulator. Gaze data was collected while participants made the crossing decisions. It was used to characterize their visual scanning strategies. Results showed that age group, limited field of view, and the presence of moving vehicles affect the way pedestrians allocate their attention in the scene. Adults tend to spend relatively more time in further peripheral areas of interest than younger pedestrians do. It was also found that the oldest child age group (11-13) demonstrated more resemblance to the adults in their visual scanning strategy, which can indicate on a learning process that originates from gaining experience and maturation. Characterization of child pedestrian eye movements can be used to determine readiness for independence as pedestrians. The results of this study, emphasize the differences among age groups in terms of visual scanning. This information can contribute to promote awareness and training directions.

Dirichlet regression model and analysis

For each scenario, five areas of interest were defined (as shown in the Figure). The close range central area was defined as the 10 meters of road in each side from the pedestrian’s point of view (AOI 3). Then symmetrically areas to the right of the center and to the left were defined. The medium right/left range (AOIs 2/4) was the part of the road distant at least 10 meter to the right/left of the point of view but less than 100 meters away. The far right/left range (AOIs 1/5) was the part of the road at least 100 meter or more to the right/left of the pedestrian point of view.

These types of data arise whenever we classify objects into disjoint categories and record their resulting relative frequencies, or partition a whole measurement into percentage contributions from its various parts.

Attempts to apply statistical methods for unconstrained data often lead to inappropriate inference.

Dirichlet regression suggested by Hijazi and Jernigan (2009) is more suitable for such cases.

How to use?

The Dirichlet regression model was fitted using DirichletReg package, in R Language. Applying a backward elimination procedure found the best fitting model has three significant main effects.

What did we find?

The dependent variable was the vector of AOIs and the independent variables were Age-group, POV and FOV; all of them were statistically significant (p <0.05). Predicted means for the percentage of time spent in each AOI for each age group based on the Dirichlet regression model are shown in the following figure and reveal differences among age groups. Note how children aged 9-10 spend more time gazing at the central area, note also the differences between mid-left and mid-right.

Predicted means (in each AOI) using Dirichlet model across all scenarios per age group

Abstract

Child-pedestrians, especially those in the age range of 5–9-years, are amongst the most vulnerable road users. These youngsters are highly represented in fatal and severe injury road crashes, despite relatively low levels of exposure to traffic. The present research investigated child and adult pedestrians’ perception of hazards utilizing a crossing decision task. Twenty-one adults (20–27 years-old) and twenty-five young-children (eight 7–9-year olds,five 9–10-year-olds and twelve 10–13-year-olds) were requested to observe traffic scene scenarios presented in a mixed reality dynamic environment simulating a typical Israeli city from a pedestrian’s perspective, and to press a response button whenever they assumed it was safe to cross. Results have shown that as pedestrians’ age and experience level increased their attentiveness towards potential hazards increases and their ability to anticipate upcoming events while engaging in a road-crossing task was enhanced. Furthermore, both the 9–10-year-olds and the 10–13-year-olds presented a less decisive performance compared to both the experienced-adult pedestrians and the 7–9-year-olds. Understanding child-pedestrians’ shortcomings in evaluating traffic situations may contribute to the effort of producing intervention techniques which may increase their attentiveness towards potential hazards and pave the way for reducing their over-involvement in road crashes. Implications for training novice road users will be discussed.

Our 3-D environment was specifically designed (B-design) for walking road users, as it provides high level of detail necessary for a walking person (i.e., not the entire urban model is built, the emphasis is on the façade). Using a 180 degrees large dome allows the feeling of immersion.

Eye tracking

A sample of a crossing scenario eye tracking pattern of a young pedestrian can be seen in the following video. Note the amount of time that the child spend viewing the cross walk itself rather than the road. My Ph.D student Hagai Tapiro is responsible for the production of this video.